code: def _gen_lcmv(active_cov, baseline_cov, common_cov):
      filters = make_lcmv(
          epochs.info,
          fwd,
          common_cov,
          reg=0.05,
          noise_cov=None,
          pick_ori="max-power",
      )
      stc_base = apply_lcmv_cov(baseline_cov, filters)
      stc_act = apply_lcmv_cov(active_cov, filters)
      stc_act /= stc_base
      return stc_act
  
file_path: mne-python/examples/inverse/evoked_ers_source_power.py
imports: import numpy
  import mne
  from mne.beamformer import apply_dics_csd, apply_lcmv_cov, make_dics, make_lcmv
  from mne.cov import compute_covariance
  from mne.datasets import somato
  from mne.minimum_norm import apply_inverse_cov, make_inverse_operator
  from mne.time_frequency import csd_morlet
label_desc: Use image node_id 2 for calling a global function with example usage: _gen_lcmv(active_cov, baseline_cov, common_cov) and returns: stc_act